Conference Agenda

The research aimed to implement quality tools in the transportation maintenance area of a poultry company in Trujillo, Peru, to reduce operating costs. The study utilized both quantitative and qualitative approaches, with a diagnostic and proactive focus. A thorough analysis of the company’s current state was conducted using quality tools such as the Ishikawa Diagram and Pareto Diagram to identify the root causes of losses, which included lack of communication with the logistics department, poor quality control in spare parts procurement, insufficient spare parts inventory, and inadequate driver training in preventive and corrective maintenance. To propose solutions, engineering methodologies such as the House of Quality (QFD), Failure Mode and Effects Analysis (FMEA), and DMAIC-Six Sigma were applied, optimizing operational processes and ensuring vehicle availability. As a result, annual losses were reduced by S/. 1,149,748.00, along with improvements in Cpk and Z-Level values for each indicator. The economic and financial evaluation revealed a Net Present Value (NPV) of S/. 3,997,565.62, an Internal Rate of Return (IRR) of 87.58%, a Payback Period (PBP) of 2.4 years and a ratio Benefit/Cost of 3, concluding that the proposal is viable for improving the company's profitability.

The objective of the research was to analyze the implementation of improvements in an automotive dealership, reducing economic losses through quality management tools. By design, this research was diagnostic and purposeful, with a formal and exact approach. A comprehensive diagnosis was carried out using the Ishikawa diagram, identifying the main root causes: lack of continuous training programs, lack of standardization of administrative processes, lack of a correct supplier evaluation system and lack of a system to record the consumption of inputs by work order or operation. The engineering methodologies used included House of Quality (QFD), Failure Mode and Effects Analysis (FMEA) and DMAIC-Six Sigma, achieving process optimization, uniformity in production, failure prevention and cost reduction. As a result, a reduction of S/ 39,480.00 in the company's losses and an increase in the Cpk and Z level values in each of the indicators were obtained. In addition, an economic/financial evaluation of the improvement proposal was carried out, obtaining a NPV of S/ 70,914.56, an IRR of 84.20%, recovering the total investment in 2.59 years, concluding that the proposal was feasible.

This systematic literature review (SLR) aims to determine how the application of Artificial Intelligence (AI) tools significantly contributes to inventory management in the industrial sector. Although the systematic review is limited by its reliance on secondary data and regional variations, it highlights the substantial innovative capacity of AI in inventory management. Future empirical studies and the development of strategies to facilitate the implementation of AI in developing regions, such as Peru, are recommended, along with investments in technology and training. This approach not only promises to refine inventory management practices, but also foster broader economic and technological advancements in these regions. The SLR confirms that Artificial Intelligence, especially through machine learning and neural networks, can significantly optimize inventory resource management in industry. Key findings highlight notable reductions in operating costs and improvements in efficiency and effectiveness, particularly in regions with advanced infrastructure. In Peru, a study on a company in the agri-food sector showed an improvement in the management of perishable products through the use of AI techniques.

The implementation of the ABIO ERP system in a swimming pool in Trujillo allowed to significantly optimize key logistics processes, achieving an average improvement of 51.63%. Among the notable results are the reduction of the purchasing cycle time from 5.00 days to 2.42 days (51.60%), order fulfillment from 12.00 days to 8.00 days (33.33%) and the reduction of the delivery cycle time from 3.00 days to 1.33 days (55.67%). Likewise, the internal shortage rate went from an average of 29.17% to 0%. These improvements are attributed to the automation and centralization of critical processes through the system, which provided better inventory management, greater efficiency in purchasing and an improvement in response capacity. The results confirm that business systems are key tools to transform and optimize logistics in sports facilities, increasing sustainability and competitiveness.

This article aims to analyze Peru's fishmeal exports to Japan following the implementation of the Free Trade Agreement (FTA) in 2012. A study was conducted covering the period from 2000 to 2023, adopting a quantitative approach, correlational scope, and non-experimental design, utilizing statistical methods such as the Student’s T-test and tools like SPSS to achieve more accurate results. The findings revealed that from 2000 to 2011, when there was no FTA in place, exports were significantly higher compared to the post-FTA period, with the lowest records observed in 2015. Similarly, a Student’s T-test was performed to compare the pre- and post-FTA periods to assess its influence. The results yielded a value lower than alpha, leading to the rejection of H0, confirming that the FTA does have an effect on the FOB value of fishmeal exports. However, this influence was negative, as the agreement introduced new requirements and permits that companies did not previously need to engage in trade. Additionally, other environmental and social factors impacted product commercialization, such as the El Niño phenomenon in 2016 and the COVID-19 pandemic in 2020.

The present study aimed to propose a reverse logistics model to improve operational efficiency in a technology sector company in Lima, Peru. The quantitative results showed significant variability in return times and a discrepancy between the actual and expected times for processing and reusing returned products. The implementation of specific engineering tools proved effective in improving these processes. Additionally, a simulation of 1000 scenarios was conducted to evaluate the economic impact of the proposals. The findings of the simulation indicated a 65.9% probability of obtaining positive economic benefits by applying the designed strategies, highlighting the financial viability and relevance of reverse logistics to improve operational efficiency. In conclusion, reverse logistics positions itself as a fundamental strategy to increase efficiency in logistics processes and sustainability in technology companies. This model can be a useful reference for other organizations seeking to improve their operational performance and commitment to sustainable practices.